Regularity of rainfall timing across Ethiopia: implications for crop production

Rainfall timing is a key parameter that farmers rely on to match the cropping season with the time window over which seasonal precipitation provides adequate soil moisture to meet plant growth demand. The unpredictability of rainfall timing affects the selection of an optimal growing season, and hence crop production in regions where rainfed agriculture (RFA) is practiced. In this study, we (a) map rainfall timing, and its interannual variability and changes over RFA areas across Ethiopia for the period 1981-2010, and (b) explore the impact of variability in rainfall timing on cereal crop production in the period 1995-2010.For the mapping of rainfall timing, we used the quasi-global CHIRPS precipitation dataset over Ethiopia. We use information entropy on monthly rainfall to define the rainfall seasonality metrics, i.e. the relative entropy and dimensionless seasonality index, and map them in space. For rainfall timing attributes, we determine the onset, cessation, and length of the wet season from LOESS-smoothed cumulative pentad rainfall anomalies for each hydrological year. Changes in seasonality metrics and rainfall timing attributes are analyzed using non-parametric methods. We show that high seasonality (unimodal rainfall regime) is located in the northern part of the Ethiopian RFA area where high annual rainfall and high relative entropy are coincident, and where the onset of the rainfall season varies between mid-April to late-June and cessation occurs between mid-September to late-October. Low seasonality in the southern part of the Ethiopian RFA area shows low relative entropy regardless of the annual rainfall total. We observed a considerable interannual variability both in seasonality and rainfall timing over the study period, especially in the onset and length of the wet season. The length of the wet season and magnitude of seasonal rainfall are predominantly controlled by the timing of rainfall onset.For the impacts of rainfall timing on crop production, we used cereal crop production data from the Central Statistical Agency of Ethiopia for the period 1995-2010 in 45 administrative zones. We carried out a parametric correlation analysis between rainfall timing and rescaled and de-trended crop production anomalies. We observe that anomalies in seasonal cereal crop production in RFA areas are significantly correlated with anomalies in rainfall onset (negatively) and the length of the wet season (positively), with a regional average production loss of 3% per pentad of late rainfall onset, and 2.7% per pentad of shorter length of the wet season. Seasonal rainfall is less strongly correlated with cereal crop production anomalies compared to the rainfall onset. These results show that the interannual variability in rainfall timing (start of the rainy season) even under present climate has strong impacts on crop yields in RFA areas in Ethiopia, and this may be exacerbated in a future climate.

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Spatiotemporal trend analysis of rainfall and temperature, and its implications for crop production

Journal of Water and Climate Change ◽

10.2166/wcc.2018.064 ◽

2018 ◽

Vol 10 (4) ◽

pp. 799-817 ◽

Cited By ~ 6

Author(s):

Tesfa Worku ◽

Deepak Khare ◽

S. K. Tripathi

Keyword(s):

Correlation Analysis ◽

Crop Production ◽

Rainfall Variability ◽

Pearson Correlation ◽

Winter Season ◽

Seasonal Rainfall ◽

Annual Rainfall ◽

Precipitation Concentration Index ◽

Mk Test ◽

The Impact

Abstract Global warming is a significant global environmental problem in the 21st century. The problem is high in developing countries, particularly sub-Saharan countries in which the majority of the population live on rainfed agriculture. The present study aimed to undertake spatiotemporal analysis of seasonal and annual rainfall and temperature and its implications. The MK test, Sen's slope and precipitation concentration index (PCI) were applied. Finally, Pearson correlation analysis between climatic variables and crop production was analysed. The Mann–Kendall test results showed that the annual and seasonal rainfall trend was highly variable. The minimum and maximum temperatures have increased by 0.8 and 1.1 °C/year, respectively. Based on PCI results, rainfall during the summer and spring seasons is moderately distributed as compared to annual and winter season rainfall. Based on these observations, the rainfall pattern and distribution of the area could be classified as irregular and erratic distribution. Results of correlation analysis between monthly and seasonal rainfall with crop production were insufficient to conclude the impact of rainfall and temperature on crop production. In view of this, the incidence of food shortage is a common occurrence. Therefore, depending on the historical trend of rainfall variability and prolonged temperature increase, appropriate coping and adaptation strategies need to be encouraged.

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Impact of changing rainfall conditions on surface and groundwater resources in an experimental watershed in Greece

Global NEST Journal ◽

10.30955/gnj.000563 ◽

2013 ◽

Vol 12 (2) ◽

pp. 119-125

Keyword(s):

Groundwater Resources ◽

Annual Runoff ◽

Annual Rainfall ◽

Rainfall Regime ◽

Winter Rainfall ◽

Rainfall Depth ◽

Rainfall Volume ◽

The Mean ◽

Groundwater Reserves ◽

The Impact

The present study concerns the impact of a change in the rainfall regime on surface and groundwater resources in an experimental watershed. The research is conducted in a gauged mountainous watershed (15.18 km2) that is located on the eastern side of Penteli Mountain, in the prefecture of Attica, Greece and the study period concerns the years from 2003 to 2008. The decrease in the annual rainfall depth during the last two hydrological years 2006-2007, 2007-2008 is 10% and 35%, respectively, in relation to the average of the previous years. In addition, the monthly distribution of rainfall is characterized by a distinct decrease in winter rainfall volume. The field measurements show that this change in rainfall conditions has a direct impact on the surface runoff of the watershed, as well as on the groundwater reserves. The mean annual runoff in the last two hydrological years has decreased by 56% and 75% in relation to the average of the previous years. Moreover, the groundwater level follows a declining trend and has dropped significantly in the last two years.

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The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

Frontiers in Agronomy ◽

10.3389/fagro.2020.615470 ◽

2020 ◽

Vol 2 ◽

Author(s):

Nathalie Colbach ◽

Sandrine Petit ◽

Bruno Chauvel ◽

Violaine Deytieux ◽

Martin Lechenet ◽

...

Keyword(s):

Crop Yield ◽

Weed Management ◽

Crop Production ◽

Yield Loss ◽

Crop Yields ◽

Cropping Systems ◽

Crop Productivity ◽

Arable Farming ◽

Herbicide Use ◽

The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

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Quantifying the impact of land degradation on crop production: the case of Senegal

Solid Earth ◽

10.5194/se-7-93-2016 ◽

2016 ◽

Vol 7 (1) ◽

pp. 93-103 ◽

Cited By ~ 8

Author(s):

B. G. J. S. Sonneveld ◽

M. A. Keyzer ◽

D. Ndiaye

Keyword(s):

Land Degradation ◽

Crop Production ◽

Crop Yields ◽

Fertilizer Application ◽

Yield Reduction ◽

Sufficient Information ◽

Persistent Problem ◽

Confounding Variables ◽

A Site ◽

The Impact

Abstract. Land degradation has been a persistent problem in Senegal for more than a century and by now has become a serious impediment to long-term development. In this paper, we quantify the impact of land degradation on crop yields using the results of a nationwide land degradation assessment. For this, the study needs to address two issues. First, the land degradation assessment comprises qualitative expert judgements that have to be converted into more objective, quantitative terms. We propose a land degradation index and assess its plausibility. Second, observational data on soils, land use, and rainfall do not provide sufficient information to isolate the impact of land degradation. We, therefore, design a pseudo-experiment that for sites with otherwise similar circumstances compares the yield of a site with and one without land degradation. This pairing exercise is conducted under a gradual refining of the classification of circumstances, until a more or less stable response to land degradation is obtained. In this way, we hope to have controlled sufficiently for confounding variables that will bias the estimation of the impact of land degradation on crop yields. A small number of shared characteristics reveal tendencies of "severe" land degradation levels being associated with declining yields as compared to similar sites with "low" degradation levels. However, as we zoom in at more detail some exceptions come to the fore, in particular in areas without fertilizer application. Yet, our overall conclusion is that yield reduction is associated with higher levels of land degradation, irrespective of whether fertilizer is being applied or not.

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Variability of rainfall in Suriname and the relation with ENSO-SST and TA-SST

Advances in Geosciences ◽

10.5194/adgeo-6-77-2006 ◽

2006 ◽

Vol 6 ◽

pp. 77-82 ◽

Cited By ~ 2

Author(s):

R. J. Nurmohamed ◽

S. Naipal

Keyword(s):

Seasonal Rainfall ◽

Annual Rainfall ◽

Time Variability ◽

Spatial Correlations ◽

Wet Season ◽

Inter Tropical Convergence Zone ◽

The Pacific ◽

Cross Correlation Analysis ◽

Rainfall Anomalies ◽

Lagged Correlation

Abstract. Spatial correlations in the annual rainfall anomalies are analyzed using principle component analyses (PCA). Cross correlation analysis and composites are used to measure the influence of sea surface temperatures anomalies (SSTAs) in the tropical Atlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. The spatial and time variability in rainfall is mainly determined by the meridional movement of the Inter-tropical Convergence Zone (ITCZ). Rainfall anomalies tend to occur fairly uniformly over the whole country. In December-January (short wet season), there is a lagged correlation with the SSTAs in the Pacific region (clag3Nino1+2=-0.63). The strongest correlation between the March-May rainfall (beginning long wet season) and the Pacific SSTAs is found with a correlation coefficient of ckNino1+2=0.59 at lag 1 month. The June-August rainfall (end part of long wet season) shows the highest correlation with SSTAs in the TSA region and is about c=-0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about clag3=0.66. The different correlations and predictors can be used for seasonal rainfall predictions.

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The impact of air–sea coupling and ocean biases on the seasonal cycle of southern West African precipitation

Climate Dynamics ◽

10.1007/s00382-019-04973-0 ◽

2019 ◽

Vol 53 (11) ◽

pp. 7027-7044

Author(s):

Caroline M. Wainwright ◽

Linda C. Hirons ◽

Nicholas P. Klingaman ◽

Richard P. Allan ◽

Emily Black ◽

...

Keyword(s):

West Africa ◽

Atlantic Ocean ◽

Crop Yields ◽

Coupled Model ◽

Dry Season ◽

Global Ocean ◽

Cmip5 Models ◽

Rainfall Regime ◽

Climate Projections ◽

The Impact

Abstract The biannual seasonal rainfall regime over the southern part of West Africa is characterised by two wet seasons, separated by the ‘Little Dry Season’ in July–August. Lower rainfall totals during this intervening dry season may be detrimental for crop yields over a region with a dense population that depends on agricultural output. Coupled Model Intercomparison Project Phase 5 (CMIP5) models do not correctly capture this seasonal regime, and instead generate a single wet season, peaking at the observed timing of the Little Dry Season. Hence, the realism of future climate projections over this region is questionable. Here, the representation of the Little Dry Season in coupled model simulations is investigated, to elucidate factors leading to this misrepresentation. The Global Ocean Mixed Layer configuration of the Met Office Unified Model is particularly useful for exploring this misrepresentation, as it enables separating the effects of coupled model ocean biases in different ocean basins while maintaining air–sea coupling. Atlantic Ocean SST biases cause the incorrect seasonal regime over southern West Africa. Upper level descent in August reduces ascent along the coastline, which is associated with the observed reduction in rainfall during the Little Dry Season. When coupled model Atlantic Ocean biases are introduced, ascent over the coastline is deeper and rainfall totals are higher during July–August. Hence, this study indicates detrimental impacts introduced by Atlantic Ocean biases, and highlights an area of model development required for production of meaningful climate change projections over the West Africa region.

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Smallholder African farms in western Kenya have limited greenhouse gas fluxes

Biogeosciences Discussions ◽

10.5194/bgd-12-15301-2015 ◽

2015 ◽

Vol 12 (18) ◽

pp. 15301-15336 ◽

Cited By ~ 3

Author(s):

D. E. Pelster ◽

M. C. Rufino ◽

T. Rosenstock ◽

J. Mango ◽

G. Saiz ◽

...

Keyword(s):

Greenhouse Gas ◽

Crop Production ◽

Crop Yields ◽

N Uptake ◽

Ghg Emissions ◽

Sub Saharan Africa ◽

N2o Emissions ◽

Vegetation Types ◽

Western Kenya ◽

The Impact

Abstract. Few field studies examine greenhouse gas (GHG) emissions from African agricultural systems resulting in high uncertainty for national inventories. We provide here the most comprehensive study in Africa to date, examining annual CO2, CH4 and N2O emissions from 59 plots, across different vegetation types, field types and land classes in western Kenya. The study area consists of a lowland area (approximately 1200 m a.s.l.) rising approximately 600 m to a highland plateau. Cumulative annual fluxes ranged from 2.8 to 15.0 Mg CO2-C ha−1, −6.0 to 2.4 kg CH4-C ha−1 and −0.1 to 1.8 kg N2O-N ha−1. Management intensity of the plots did not result in differences in annual fluxes for the GHGs measured (P = 0.46, 0.67 and 0.14 for CO2, N2O and CH4 respectively). The similar emissions were likely related to low fertilizer input rates (≤ 20 kg ha−1). Grazing plots had the highest CO2 fluxes (P = 0.005); treed plots were a larger CH4 sink than grazing plots (P = 0.05); while N2O emissions were similar across vegetation types (P = 0.59). This case study is likely representative for low fertilizer input, smallholder systems across sub-Saharan Africa, providing critical data for estimating regional or continental GHG inventories. Low crop yields, likely due to low inputs, resulted in high (up to 67 g N2O-N kg−1 aboveground N uptake) yield-scaled emissions. Improving crop production through intensification of agricultural production (i.e. water and nutrient management) may be an important tool to mitigate the impact of African agriculture on climate change.

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Agroresource potential and rationale for irrigation North-Central Steppe of Ukraine

Interdepartmental thematic scientific collection "Agriculture" ◽

10.31073/zem.90.71-76 ◽

2016 ◽

Vol 1 (90) ◽

pp. 71-76

Author(s):

Y. Soroka ◽

Y.A. Tarariko ◽

R.V. Saydak

Keyword(s):

Crop Rotation ◽

Crop Production ◽

Crop Yields ◽

Climatic Conditions ◽

Hydrothermal Conditions ◽

North Central ◽

Intensive Farming ◽

Phosphorus And Potassium ◽

Major Factors ◽

The Impact

The purpose of research - a comprehensive assessment of the potential agroresource North-Central Steppe of Ukraine, set limitipuyuschie factors to improve the productivity of agriculture. During the robot conventional research methods were used: field, laboratory, analytical, comparative, kompyuternoy simulation modeling, and system generalization of the results. Experiental part held in a stationary field experiment Zaporozhye experimental station Of Institute oil culture NAAS Studies have shown that the systematic application of fertilizers on a range of agro, chemical, physical, agrohimichesih indicators studied soil has Visokiy potential fertility. Surfacing Systems of soil on crop rotation productivity impact is immaterial. One can only note the trend for the most minor ways of loosening the soil with mulch. The test crop rotation composition simulates one of the most intensive farming options. Indicators of productivity and the variation coefficient of variation it indicates a fairly low level of realization of the potential fertility of chernozem ordinary, which is explained on the one hand, the steady downward trend in the annual water balance, on the other hand, promotion of a balance of humus, nitrogen, phosphorus and potassium fertilizers at the studied systems. The dependence of the yield of the agro-climatic conditions considered by the example of the main cereal region - winter wheat. It was found that the greatest impact on the implementation of crop production potential are hydrothermal conditions of May - June. Analysis of the results of research allowed to evaluate the potential agroresource North Steppe and to establish the impact of the major factors in the formation of crop yields. Irrigation in this zone is the most important factor for improving productivity of crops, and its implementation in 70% of rotations may increase the productivity of not less than 1.8 times.

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THE POTENTIAL IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN WEST AFRICA: A BIO-ECONOMIC MODELING APPROACH

Climate Change Economics ◽

10.1142/s2010007819500155 ◽

2019 ◽

Vol 10 (04) ◽

pp. 1950015

Author(s):

BORIS O. K. LOKONON ◽

AKLESSO Y. G. EGBENDEWE ◽

NAGA COULIBALY ◽

CALVIN ATEWAMBA

Keyword(s):

Climate Change ◽

Land Use ◽

Crop Production ◽

Crop Yields ◽

Negative Impact ◽

Economic Modeling ◽

Climate Conditions ◽

Impact Of Climate Change ◽

Potential Impact ◽

The Impact

This paper investigates the impact of climate change on agriculture in the Economic Community of West African States (ECOWAS). To that end, a bio-economic model is built and calibrated on 2004 base year dataset and the potential impact is evaluated on land use and crop production under two representative concentration pathways coupled with three socio-economic scenarios. The findings suggest that land use change may depend on crop types and prevailing future conditions. As of crop production, the results show that paddy rice, oilseeds, sugarcane, cocoa, coffee, and sesame production could experience a decline under both moderate and harsh climate conditions in most cases. Also, doubling crop yields by 2050 could overall mitigate the negative impact of moderate climate change. The magnitude and the direction of the impacts may vary in space and time.

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Global Patterns of the Contributions of Storm Frequency, Intensity, and Seasonality to Interannual Variability of Precipitation

Journal of Climate ◽

10.1175/jcli-d-14-00653.1 ◽

2015 ◽

Vol 29 (1) ◽

pp. 3-15 ◽

Cited By ~ 13

Author(s):

Stephen P. Good ◽

Kaiyu Guan ◽

Kelly K. Caylor

Keyword(s):

Interannual Variability ◽

Amazon Basin ◽

Cross Correlation ◽

Rainfall Variability ◽

Precipitation Variability ◽

Individual Variability ◽

Precipitation Event ◽

Annual Rainfall ◽

Eastern United States ◽

Wet Season

Abstract Interannual variation in precipitation totals is a critical factor governing the year-to-year availability of water resources, yet the connection between interannual precipitation variability and underlying event- and season-scale precipitation variability remains unclear. In this study, tropical and midlatitude precipitation characteristics derived from extensive station records and high-frequency satellite observations were analyzed to attribute the fraction of interannual variability arising as a result of individual variability in precipitation event intensity, frequency, and seasonality, as well as the cross-correlation between these factors at the global scale. This analysis demonstrates that variability in the length of the wet season is the most important factor globally, causing 52% of the total interannual variability, while variation in the intensity of individual rainfall events contributes 31% and variability in interstorm wait times contributes only 17%. Spatial patterns in the contribution of each of these intra-annual rainfall characteristics are informative, with regions such as Indonesia and southwestern North America primarily influenced by seasonality, while regions such as the eastern United States, central Africa, and the upper Amazon basin are strongly influenced by storm intensity and frequency. A robust cross-correlation between climate characteristics is identified in the equatorial Pacific, revealing an increased interannual variability over what is expected based on the variability of individual events. This decomposition of interannual variability identifies those regions where accurate representation of daily and seasonal rainfall statistics is necessary to understand and correctly model rainfall variability at longer time scales.

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